{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 分类问题性能评估\n",
    "- 错误率 | 精度(`accuracy`)：被错误 | 正确预测的样本数占总样本的比率\n",
    "    \n",
    "对于二分类：\n",
    "- 查准率(`precision`)：预测为正样本的样本中的准确率\n",
    "- 查全率(`recall`)：正样本的预测准确率\n",
    "- `F1 score`：\n",
    " $F_1=\\frac{2}{\\frac{1}{precision}+\\frac{1}{recall}}$\n",
    " \n",
    "为什么需要这些指标：\n",
    "- 数据不平衡，如 98% 邮件都是垃圾邮件，模型检测是否垃圾邮件？将所有邮件都归为垃圾邮件，此时精度仍有 98%\n",
    "- 例如针对儿童的视频分类器，该分类器可能误屏蔽很多好视频(`low recall`)，但是坏视频的准确率必须要很高(`high precision`)\n",
    "     \n",
    "`Precision/Recall Tradeoff`，如下图所示：十个数字，预测为 5 的概率从左至右依次增大，当判断是否为 5 的阈值改变时，对应的 `precision/recall` 相应会发生变化，`precision` 越大，`recall` 越小，反之也成立\n",
    "![](images/DecisionThreshold_PrecisionRecallTradeoff.png)\n",
    "\n",
    " \n",
    " \n",
    " \n",
    "`ROC` 曲线，纵轴是真正例率(`True Positive Rate`)，横轴是假正例率(`False Positive Rate`)\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TP、TN、FP、FN\n",
    "def getTP(y_true, y_pred):\n",
    "    return sum((y_true == 1) & (y_pred == 1))\n",
    "\n",
    "\n",
    "def getTN(y_true, y_pred):\n",
    "    return sum((y_true == 0) & (y_pred == 0))\n",
    "\n",
    "\n",
    "def getFP(y_true, y_pred):\n",
    "    return sum((y_true == 0) & (y_pred == 1))\n",
    "\n",
    "\n",
    "def getFN(y_true, y_pred):\n",
    "    return sum((y_true == 1) & (y_pred == 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# confusion matrix\n",
    "def confusion_matrix(y_true, y_pred):\n",
    "    TP = getTP(y_true, y_pred)\n",
    "    TN = getTN(y_true, y_pred)\n",
    "    FP = getFP(y_true, y_pred)\n",
    "    FN = getFN(y_true, y_pred)\n",
    "    return np.array([[TN, FP], [FN, TP]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 精度\n",
    "def accuracy(y_true, y_pred):\n",
    "    return sum(y_true == y_pred) / len(y_true)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True, False,  True, False,  True, False,  True,  True,\n",
       "        True])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查全率：所有正样本中，正确预测的比率\n",
    "def recall(y_true, y_pred):\n",
    "    TP = getTp(y_true, y_pred)\n",
    "    FN = getFN(y_true, y_pred)\n",
    "    return TP / (TP + FN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 查准率：预测为正的所有样本中，正样本的比率\n",
    "def precision(y_true, y_pred):\n",
    "    TP = getTP(y_true, y_pred)\n",
    "    FP = getFP(y_true, y_pred)\n",
    "    return TP / (TP + FP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# f1 score：是查全率与查准率的调和平均值，其值越大越好\n",
    "def f1_score(y_true, y_pred):\n",
    "    r = recall(y_true, y_pred)\n",
    "    p = precision(y_true, y_pred)\n",
    "    return 2 * r * p / (r + p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "精度为   : 0.7\n",
      "查准率   : 0.6666666666666666\n",
      "查全率   : 0.8\n",
      "F1 score: 0.7272727272727272\n"
     ]
    }
   ],
   "source": [
    "# sklearn API\n",
    "from sklearn.metrics import precision_score, recall_score, f1_score, accuracy_score, accuracy_score\n",
    "\n",
    "y = [0] * 5 + [1] * 5\n",
    "y_pred = [0, 0, 1, 0, 1, 1, 0, 1, 1, 1]\n",
    "\n",
    "print(\"精度为   :\", accuracy_score(y, y_pred))\n",
    "print(\"查准率   :\", precision_score(y, y_pred))\n",
    "print(\"查全率   :\", recall_score(y, y_pred))\n",
    "print(\"F1 score:\", f1_score(y, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ROC 曲线\n",
    "# 得到预测概率后，设定阈值，得到预测标签；\n",
    "# 改变阈值，性能指标值就会发生变化\n",
    "# 当没有设定阈值时，如何评估模型?\n",
    "import numpy as np\n",
    "from sklearn.metrics import roc_curve\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "y_true = np.array([1, 1, 2, 2])\n",
    "y_score = np.array([0.1, 0.4, 0.35, 0.8])\n",
    "\n",
    "fpr, tpr, thresholds = roc_curve(y_true, y_score, pos_label=2)\n",
    "# 返回每个阈值对应的真阳性率、假阳性率及阈值列表\n",
    "\n",
    "\n",
    "def plot_roc_curve(fpr, tpr, label=None):\n",
    "    plt.plot(fpr, tpr, linewidth=2, label=label)\n",
    "    plt.plot([0, 1], [0, 1], 'k--')\n",
    "    plt.axis([0, 1, 0, 1])\n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "\n",
    "\n",
    "plot_roc_curve(fpr, tpr)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 逻辑回归\n",
    "- 逻辑回归用于解决分类问题，而不是回归问题；基本思想是：对数据的分类边界建立回归公式，以此进行分类\n",
    "    - 逻辑回归的本质： 极大似然估计\n",
    "    - 逻辑回归的激活函数：Sigmoid\n",
    "    - 逻辑回归的代价函数：交叉熵\n",
    "\n",
    "\n",
    "- 逻辑回归评估样本属于某一类的概率，通常概率大于 `50%` ，模型就会预测该样本属于该类，否者不属于\n",
    "- 逻辑回归模型：\n",
    "$$\\hat{p}=h_\\theta(X)=\\sigma(\\theta^T\\cdot X)\\quad \\sigma(t)=\\frac{1}{1+exp(-t)}$$\n",
    "$$\\hat{y}=\\begin{cases} 0\\qquad \\hat{p}<0.5,\\\\1\\qquad  \\hat{p}\\geq 0.5.\\end{cases}$$\n",
    "- 损失函数：\n",
    "    - 模型在单个样本上的损失：\n",
    "        $$c(\\theta)=\\begin{cases}-log(\\hat{p})\\qquad y=1\\\\-log(1-\\hat{p})\\ \\ y=0\n",
    "    \\end{cases}$$\n",
    "        - 当 $t$ 接近 $0$ ，$-log(t)$ 变得非常大；即当模型预测错误，样本属于正确类别的概率很低，损失越大。\n",
    "    - 损失函数：\n",
    "        $$J(\\theta)=-\\frac{1}{m}\\sum_{i=1}^m [y^{(i)}log(\\hat{p}^{(i)})+(1-y^{(i)})log(1-\\hat{p}^{(i)})]$$\n",
    "        - 逻辑回归损失函数没有完全解，但为凸函数，梯度下降法保证可以找到最小值\n",
    "    - 损失函数的梯度：\n",
    "    $$\\frac{\\partial}{\\partial \\theta_j}J(\\theta)=\\frac{1}{m}\\sum_{i=1}^{m}(\\sigma(\\theta^T\\cdot X^{(i)})-y^{(i)})x_j^{(i)}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-------------------------\n",
    "\n",
    "```\n",
    "class sklearn.linear_model.LogisticRegression(penalty=’l2’, \n",
    "                                              dual=False, \n",
    "                                              tol=0.0001, \n",
    "                                              C=1.0, \n",
    "                                              fit_intercept=True, \n",
    "                                              intercept_scaling=1, \n",
    "                                              class_weight=None, \n",
    "                                              random_state=None, \n",
    "                                              solver=’warn’, \n",
    "                                              max_iter=100, \n",
    "                                              multi_class=’warn’, \n",
    "                                              verbose=0, \n",
    "                                              warm_start=False, \n",
    "                                              n_jobs=None, \n",
    "                                              l1_ratio=None)\n",
    "```\n",
    "- 参数：\n",
    "    - penalty：正则化类型，l1 通过系数矩阵的系数绝对值之和， l2 通过系数矩阵系数的平方和，底层使用不同的数学求解器\n",
    "    - C：惩罚系数，正值， 值越大，系数越接近于0\n",
    "    - class_weight：类别权重，默认为None，即不给定时，所有类别权重为 1；或词典形式`{class_label: weight}`；或 ‘balanced’，`n_samples / (n_classes * np.bincount(y))`\n",
    "    - solver：底层的求解算法\n",
    "    - max_iter：最大迭代次数\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Softmax Regression\n",
    "- 多分类模型，或多维逻辑回归；\n",
    "- 首先计算出样本对每个类别的权重，然后 `softmax function` 求出样本属于每一类的概率，最后输出最大概率对应的类别\n",
    "    - $S_k(X)=\\theta_k^T\\cdot X$\n",
    "    - $\\hat{p}_k=\\sigma(S(X))_k=\\frac{exp(S_k(X))}{\\sum_{j=1}^k exp(S_j(X))}$\n",
    "    - $\\hat{y}=argmax_{k}\\ \\sigma(S(X))_k=argmax_{k}(\\theta_k^T\\cdot X)$\n",
    "- 交叉熵损失函数：\n",
    "$$J(\\Theta)=-\\frac{1}{m}\\sum_{i=1}^{m}\\sum_{k=1}^Ky_k^{(i)}log(\\hat{p}_k^{(i)})$$ \n",
    "    - 样本共有 $K$ 个类别\n",
    "    - $y_k^{(i)}$ 为 1 ，当样本 $i$ 属于第 $k$ 类时，否者为 0\n",
    "- 类别 $k$ 的梯度向量：\n",
    "$$\\nabla_{\\theta_k}J(\\Theta)=\\frac{1}{m}\\sum_{i=1}^m(\\hat{p}_k^{(i)}-y_k^{(i)})X^{(i)}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[6.38014896e-07, 5.74929995e-02, 9.42506362e-01]])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "iris=load_iris()\n",
    "X=iris.data[:,(2,3)]\n",
    "y=iris.target\n",
    "\n",
    "softmax_reg=LogisticRegression(multi_class='multinomial',solver='lbfgs',C=10)\n",
    "softmax_reg.fit(X,y)\n",
    "\n",
    "softmax_reg.predict_proba([[5,2]])\n",
    "# 三分类，样本 [5,2] 属于每一类的概率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 多分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f845d3a9b90>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import linear_model, datasets\n",
    "\n",
    "# 三分类\n",
    "iris = datasets.load_iris()\n",
    "x = iris.data[:, :2]\n",
    "y = iris.target\n",
    "\n",
    "plt.scatter(x[:, 0], x[:, 1], c=y, edgecolors='k', cmap=plt.cm.Paired)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/yangbin7/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/home/yangbin7/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=100000.0, class_weight=None, dual=False,\n",
       "                   fit_intercept=True, intercept_scaling=1, l1_ratio=None,\n",
       "                   max_iter=100, multi_class='warn', n_jobs=None, penalty='l2',\n",
       "                   random_state=None, solver='warn', tol=0.0001, verbose=0,\n",
       "                   warm_start=False)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 逻辑回归的多分类\n",
    "clf = linear_model.LogisticRegression(C=1e5)\n",
    "clf.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "h = 0.02\n",
    "x_min, x_max = x[:, 0].min() - 0.5, x[:, 0].max() + 0.5\n",
    "y_min, y_max = x[:, 1].min() - 0.5, x[:, 1].max() + 0.5\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
    "\n",
    "z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "z = z.reshape(xx.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1, figsize=(8, 6))\n",
    "plt.pcolormesh(xx, yy, z, cmap=plt.cm.Paired)\n",
    "\n",
    "plt.scatter(x[:, 0], x[:, 1], c=y, edgecolors='k', cmap=plt.cm.Paired)\n",
    "plt.xlabel('Sepal length')\n",
    "plt.ylabel('Sepal width')\n",
    "\n",
    "plt.xlim(xx.min(), xx.max())\n",
    "plt.ylim(yy.min(), yy.max())\n",
    "plt.xticks(())\n",
    "plt.yticks(())\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.datasets import make_multilabel_classification\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.preprocessing import LabelBinarizer\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.cross_decomposition import CCA\n",
    "\n",
    "\n",
    "def plot_hyperplane(clf, min_x, max_x, linestyle, label):\n",
    "    w = clf.coef_[0]\n",
    "    a = -w[0] / w[1]\n",
    "\n",
    "    xx = np.linspace(min_x - 5, max_x + 5)\n",
    "    yy = a * xx - (clf.intercept_[0]) / w[1]\n",
    "\n",
    "    plt.plot(xx, yy, linestyle, label=label)\n",
    "\n",
    "\n",
    "def plot_subfigure(x, y, subplot, title, transform):\n",
    "    if transform == 'pca':\n",
    "        x = PCA(n_components=2).fit_transform(x)\n",
    "    elif transform == 'cca':\n",
    "        x = CCA(n_components=2).fit(x, y).transform(x)\n",
    "    else:\n",
    "        raise ValueError\n",
    "\n",
    "    min_x = np.min(x[:, 0])\n",
    "    max_x = np.max(x[:, 0])\n",
    "    min_y = np.min(x[:, 1])\n",
    "    max_y = np.max(x[:, 1])\n",
    "\n",
    "    classif = OneVsRestClassifier(SVC(kernel='linear'))\n",
    "    classif.fit(x, y)\n",
    "\n",
    "    plt.subplot(2, 2, subplot)\n",
    "    plt.title(title)\n",
    "\n",
    "    zero_class = np.where(y[:, 0])\n",
    "    one_class = np.where(y[:, 1])\n",
    "\n",
    "    plt.scatter(x[:, 0], x[:, 1], s=40, c='gray', edgecolors=(0, 0, 0))\n",
    "    plt.scatter(x[zero_class, 0],\n",
    "                x[zero_class, 1],\n",
    "                s=160,\n",
    "                edgecolors='b',\n",
    "                facecolors='none',\n",
    "                linewidth=2,\n",
    "                label='Class 1')\n",
    "    plt.scatter(x[one_class, 0],\n",
    "                x[one_class, 1],\n",
    "                s=80,\n",
    "                edgecolors='orange',\n",
    "                facecolors='none',\n",
    "                linewidth=2,\n",
    "                label='Class 2')\n",
    "\n",
    "    plot_hyperplane(classif.estimators_[0], min_x, max_x, 'k--',\n",
    "                    'Boundray\\nfor class1')\n",
    "    plot_hyperplane(classif.estimators_[1], min_x, max_x, 'k--',\n",
    "                    'Boundray\\nfor class2')\n",
    "\n",
    "    plt.xticks(())\n",
    "    plt.yticks(())\n",
    "\n",
    "    plt.xlim(min_x - 0.5 * max_x, max_x + 0.5 * max_x)\n",
    "    plt.ylim(min_y - 0.5 * max_y, max_y + 0.5 * max_y)\n",
    "\n",
    "    if subplot == 2:\n",
    "        plt.xlabel('First principal component')\n",
    "        plt.ylabel('Second principal component')\n",
    "        plt.legend(loc=\"upper left\")\n",
    "\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "X, Y = make_multilabel_classification(n_classes=2,\n",
    "                                      n_labels=1,\n",
    "                                      allow_unlabeled=True,\n",
    "                                      random_state=1)\n",
    "\n",
    "plot_subfigure(X, Y, 1, \"With unlabeled samples + CCA\", \"cca\")\n",
    "plot_subfigure(X, Y, 2, \"With unlabeled samples + PCA\", \"pca\")\n",
    "\n",
    "x, y = make_multilabel_classification(n_classes=2,\n",
    "                                      n_labels=1,\n",
    "                                      allow_unlabeled=False,\n",
    "                                      random_state=1)\n",
    "\n",
    "plot_subfigure(x, y, 3, \"Without unlabeled samples+CCA\", \"cca\")\n",
    "plot_subfigure(x, y, 4, \"Without unlabeled samples+PCA\", \"pca\")\n",
    "\n",
    "plt.subplots_adjust(.04, .02, .97, .94, .09, .2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "toc": {
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